Course Outcomes Semester - II



Semester-II, Paper-II:

Course Title
Course Type
HPW
Credits
Probability Distributions
(Theory + Practical)
DSC-2B
4(Th)+2(Pr)
4+1
         
Upon successful completion of this course , students will be able to:

ü Use discrete and continuous probability distributions, including requirements, mean and variance, and making decisions.
ü Define binomial outcomes and compute probability of getting X successes in N trials.
ü Identify the characteristics of different discrete and continuous distributions.
ü Identify the type of statistical situation to which different distributions can be applied.
ü Use Poisson, exponential distributions to solve statistical problems..
ü Use the normal probability distribution including standard normal curve calculations of appropriate areas.
ü Use different distributions to solve simple practical problems.
ü Analyze Statistical data using MS-Excel.


Comments

Post a Comment

Popular posts from this blog

B.Com- II yr, Semester-IV, Business Statistics - II Syllabus

Paper: (BC 406): BUSINESS STATISTICS-II Paper: BC 406 Max. Marks: 100 HPW: 4 with  Credits: 4 OBJECTIVE: To inculcate analytical and computational ability among the students. UNIT-I: REGRESSION: Introduction - Linear and Non Linear Regression – Correlation Vs. Regression - Lines of Regression – Derivation of Line of Regression of Y on X - Line of Regression of X on Y - Using Regression Lines for  Prediction. UNIT-II: INDEX NUMBERS: Introduction - Uses - Types - Problems in the Construction of Index Numbers - Methods of Constructing  Index Numbers - Simple and Weighted Index Number (Laspeyre - Paasche, Marshall – Edge worth) – Tests of Consistency of Index Number: Unit Test - Time Reversal Test - Factor Reversal Test –  Circular Test - Base Shifting - Splicing and Deflating of Index Numbers. UNIT-III: TIME SERIES: Introduction - Components – Methods-Semi Averages - Moving Averages – Least Square Method – Deseasonalisation of Data – Uses and Limitations of Ti
Read more

Sampling Theory: MCQ

1.A sample consists of: (a)   All units of the population (b) 50 per cent units of the population (c) 5 per cent units of the population (d) Any fraction of the population 2. Sampling is inevitable in the situation(s):           (a) Blood test of a person           (b) When the population is infinite           (c) Testing of life of dry battery cells           (d) All the above 3. The number of possible samples of size n out of N population    units without replacement is: (a) Nc n             (b) (N) n               (c) n²                    (d) N! 4. The number of possible samples of size two from a population of 4    units under SRSWOR:             (a) 6                          (b) 4                                 (c) 8                         (d) 16 5. Probability of drawing a unit at each selection remains same in:            (a) SRSWOR                   (b) SRSWR                  (c) Both (a) and (b)          (d)None of them 6. Probabil
Read more

Unit wise important questions

Image
B.Sc (M.S.Cs)-III Year                                          Subject: Statistics, Paper: III UNIT-I 1. Explain the principal steps involved in a sample survey. 2. (i).  Distinguish between SRSWOR and SRSWR with examples. (ii). In SRSWOR, show that the Probability of selecting a specified unit  at   any given draw is equal to the probability of  selecting it at the first draw. 3. In SRSWOR, show that        (i). Sample mean square is an unbiased estimator of population mean square.        (ii). V( n )= {(N-n)/Nn} S 2      4. Explain the purpose of stratification in sample survey.         Show that V( n ) R  V( st ) prop in usual notations.         5. In usual notations, prove that the systematic sample mean is more efficient     than the mean of a simple random sample taken without replacement      if   S 2 wsy  S 2 .  6. With the usual notations, Prove that  V( st ) opt  V( st ) prop  V( n ) wor  7. In Neyman allocation of stratified random
Read more